Analysis of the effectiveness of national renewable energy policies: A case of photovoltaic policies

Renewable and Sustainable Energy Reviews 79 (2017) 669–680

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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Analysis of the effectiveness of national renewable energy policies: A case of photovoltaic policies

MARK

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Hamed Hafezniaa, Alireza Aslania, , Sohail Anwarb, Mahdis Yousefjamalic a b c

Renewable Energies and Environment Department, Faculty of New Sciences and Technologies, University of Tehran, Iran Altoona College, Pennsylvania State University, USA Graduate School of Management and Planning, Tehran, Iran

A R T I C L E I N F O

A BS T RAC T

Keywords: Photovoltaic Energy policy Policy assessment Renewable energy

Although fossil fuels are the main sources of power generation, they are losing their advantages because of their limitations and environmental and economic concerns. As an alternative, the development of renewable energy technologies is one of the important strategies. Therefore, governments have been encouraging the deployment of renewable energy resources. However, there are gaps between achievements and targets. As most of the national renewable energy development policies are formulated in the entire country equally, the outputs and achievements are different depending on the geographical characteristics, social and economic capabilities of the regions. The purpose of the present study is the analysis and the evaluation of the effectiveness of the equal national renewable energy policy in the different regions of a country. This research focuses on the idea that whether the codification of energy policies according to the local circumstances of each region can result in a greater efficiency of such policies. An innovative framework is presented to categorize the government policies based on the geographical, technical and socio-economic indicators. To examine the presented framework, it is implemented as a case study.

1. Introduction Security of energy supply is one of the important concerns of the governments. Energy security concerns along with consumption growth are rapidly rising in importance in the world. In response, renewable energy resources (RERs) are offering a viable option for the reduction of dependency on imported energy and providing social and environmental benefits. RERs are typically used in three main frames: electricity generation, bio-products, and in heating/cooling systems. To attain success in promoting renewable energy (RE) deployment, different policies have been formulated by the governments, such as, reducing tariffs, standard portfolio, tax credits, pricing rules, production incentives, and required quota. The important point is the similarity of policies that is implemented in the entire country. Nevertheless, the success of promotional policies from RERs is not considerable compared to other energy policies. The noticeable point is that energy policies are adopted and implemented identically for all parts of the countries having a unitary government. In other words, the socio-economic capacities and the geographical characteristics of different regions of the country are not taken into consideration in the procedures of energy policy-making.

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Corresponding author. E-mail address: [email protected] (A. Aslani).

http://dx.doi.org/10.1016/j.rser.2017.05.033 Received 28 May 2016; Received in revised form 5 March 2017; Accepted 10 May 2017 1364-0321/ © 2017 Elsevier Ltd. All rights reserved.

The case study of the current research, Iran, it has always executed equal renewable energy policies in the entire country and this has led to the failures in the RE projects [1]. Fig. 1 shows, unlike the global trends, the total installed capacity of PV power plants in Iran have not only undergone any increase but it has also decreased between 2006 and 2013. The purpose of this research is to develop a framework to determine whether the codification of energy policies according to the local circumstances of each region can result in a greater efficiency of such policies and in doing so, consequently, render RE business feasible? Therefore, we present our framework for the investigation of photovoltaic policies and then, we evaluate its implementation for the case study, Iran. To achieve the purpose, we design the following research questions: 1. What variables can affect the successful implementation of a utilityscale photovoltaic project? The survey of the extant literature indicates that the successful implementation of a photovoltaic project depends on three variables, namely the climatic, the local socio-economic conditions and the

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Fig. 1. Total installed capacity of PV power plants in Iran, 2006–2013 [70].

only way to reach sustainable development is the maximal consumption of renewables; for instance, about 100% and 96.6% of the demanded electricity in Norway and Iceland were supplied by sustainable resources in 2010 [4]. According to former future energy policies, the development strategies of renewable energy (RE) are an important part of US energy security action plan. There are also noticeable efforts and long-term plans in other countries in Europe, Asia, and North America for the utilization of RERs. Since the renewable energy (RE) industry offers a profitable future, various business opportunities exist for investment in this industry. However, the economic utilization of a renewable portfolio, in particular in new technologies such as wind power and solar power, has faced challenges that affect investors and public sector decisions.

technical design. In line with this, Iran's provinces based on climatic, technical, and socio-economic aspects are investigated to determine the priority of them for the purpose of making investments in the photovoltaic projects. 2. Why has the implementation of equal photovoltaic policies for the different regions in Iran been ineffective? This question can be answered through independently analyzing the results of Iran's provinces prioritization in terms of the three aspects, namely climatic, technical and socio-economic faucets. 3. Is it possible to promote the deployment of renewable energy technologies by defining supportive policies and strategies in a specific manner unique to each of the provinces?

2.2. Renewable energy challenges

The work is organized based on the following sections. First, the importance and the challenges of renewable energy utilization are reviewed. Then, the experiences of renewable energy policies in the different countries, in particular for PV supportive policies are evaluated. After that, the research problem and descriptive hypothesis are presented. Thereafter, the suggested framework is introduced. Finally, the framework is simulated for a case study and a practical example of the proposed strategies is mentioned.

Despite several policies and plans for the successful diffusion of RE utilization, achievements have gaps with respect to targets. Our studies show that more than 70% of the patents that are related to RE technologies have not had any place in the market [5]. This means there are barriers for the development of RE technologies, products, and service [6–8]. Table 1 shows the most important barriers of RE technologies [9]. Due to the importance of the security of energy supply for governments as one of the main factors of robust economic growth, and because of environmental and feasibility limitations of fossil fuels, strong public support exists for replacements strategies such as the diffusion of RE technologies utilization [10].

2. Literature review 2.1. The importance of renewable energy Energy demand is growing fast because of the economic and social development in the world. To achieve the secure and safe supply of energy, governments are faced with challenges such as fluctuating fossil fuel prices, increasing global demand for energy, uncertainties in oil and natural gas supplies arising from geopolitical concerns, and global warming [2]. In response, policy makers have suggested and developed various strategies such as the upstream investment of producers, utilizing domestic and local natural resources, long-term contracting at premium prices, diversifying fuels and suppliers, developing dual fuel technologies, the decentralized forms of utilization [3]. On the other hand, the environmental, technological, and political dangers of nuclear energy illustrate the necessity of utilizing other reliable sources. Among different strategies, policy makers and researchers have paid special attention to the role of diversification strategies (sources/ suppliers) and the utilization of renewable energy resources (RERs). Because of local availability, the free, clean, eco-friendly aspect and the sustainability of RERs, economists and policy makers admit that the

2.3. Review of PV policies in the countries Almost all countries have invested on the deployment of RERs. However, China, United States, Japan, United Kingdom and India were top five countries in terms of RE investment in 2015 [11]. In the regional level, countries have also special plans for the diffusion of RE technologies. As an example, European Union has the ambitious plans of RE development for its members. They should increase the share of RE by 20% by 2020 [12]. In particular, Germany, Spain, Italy, Switzerland, Finland, and Sweden have major green power market in Europe. Because of the well-defined government incentives, wind power industry, as an example, has reached to explosive growth in terms of cumulative installed capacity and manufacturing in China from 2005 [13]. The total installed wind power capacity was 168,690 MW in China at the end of 2016 with the highest share of installed capacity in the world (34.7%) [14]. The success in the commercialization of RE technologies in China is because of several 670

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incentive cash reduce the initial cost of PV installation [29]. According to Kwan (2012), received solar radiation, the cost of electricity, and the amount of state-level financial incentives are the effective factors on solar PV adoption [30]. Mendonça et al. (2010) have found that the policies of the feed-in tariff (FiT) can be successfully implemented by governments to grow the installed RE electricity generation capacity in the local areas [31]. White et al. (2013) have presented FIT tables in New Zealand to facilitate network communication process and provide a stable environment for future potential investors and increase local installed solar capacity [32]. Shrimali et al. (2017) examined the effectiveness of Indian RE policies at federal level by using financial models. They indicated debt-related policies are the most important ones for cost-effectiveness in the long-term [33]. Despite the above issues, the effectiveness of PV policies based on the regional capacities has not been considered in the research studies.

Table 1 Important barriers to successful RE businesses [9]. Barrier or limitation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Budgetary limitations Lack of information on RE market, demand, and potential Failure in commercialization plans Ambiguous policies and regulations Cost of RE utilization for end-user Conversion efficiency of RERs Operation and maintenance costs Lack of mechanisms to provide modern and efficient energy services in rural areas Inadequate incentive for RERs utilization compared to fossil fuels(e.g., taxation, tariffs, substitutes, and feed in) Absence of policies related to promotion RE energy Low public awareness of RERs Lack of familiarity with green certificates and standards Lack of robust planning of RE development at the strategic and practical levels Low storage capacity of RE technologies compared to fossil fuels Gaps between research projects and needs of the market Poor quality of some RE technologies and utilization Lack of specialized and skilled manpower in RE industry Dominance of old fossil energy-inefficient technologies Social and environmental barriers via beneficiary groups Location selection (Site selection) Inadequate coordination among the various stakeholders

2.5. Problem statement Due to the high competition between RE technologies and markets with fossil fuels and other energy sources (e.g., nuclear), successful RE utilization needs the governments’ supports. This means that the governments have to develop encouragement policies to speed up RE utilization programs. Traditionally, the policies are developed, delivered, and implemented similar within the geographic boundaries. Thus, the defined policies have similar behavior in different states and provinces. However, the potential of RE utilization is highly dependent on geographical conditions and the level of local readiness and regional capabilities. This is important in particular for large countries with various geographical conditions and the different levels of development. Therefore, despite the allocated budgets and time, the effectiveness and success of RE policies are not similar in the entire country. In other words, if the supportive RE policies are announced and implemented equally across the geographical areas of a country, the efficiency of this policy would not be the same. This means, it is necessary for the government to consider a portfolio of RE policies. The aim of this research is to evaluate the effectiveness of same RE government policies. After that, an innovation framework is presented and simulated for a case study.

government incentives such as R & D support, localization policy, feedin tariff policy, providing credit lines and loans to wind power enterprises and exporters, etc. [15]. The Indian government has also formulated several policies to support the expansion of RE commercialization [16]. As an example, the capital subsidy policies are during the initial stages of RE projects. Indeed, tax incentive accelerates the development of RE products and projects. Other policies, such as fiscal and financial incentives, also exist to encourage the RE producers and manufacturers to increase their market and profit in the energy industry. Germany is also a world leader in the development and installation of RE, in particular photovoltaic. The country has established an international commercialization cooperation where manufacturers, businesses, consultants, and R & D organizations share their experience with other countries. In particular, for the case of commercialization in the PV industry, Germany has supportive mechanisms such as banking and financing supports (even during the economic crisis) in order to speed the new PV products, technologies, and services [17]. More than 25 PV inverter manufacturers, 65 companies with PV productions, 45 PV equipment manufacturers and many manufacturers of materials for PV modules and system components are working in Germany. Just in 2012, around 110,000 workers were employed in the PV industry in Germany [18,19]. Another example is Canada that applies reduced tariffs and providing state incentives for PV.

3. Research method Based on the above problem statement, a descriptive hypothesis is defined as follows: "The effectiveness of government supportive policies for the exploitation of RE depends on the socio-economic, climatic, and technical aspects.". To test the hypothesis, a conceptual framework is designed and implemented in a case study (Iran). Fig. 2 shows the conceptual framework of this research study. According to the figure, the effectiveness of government supportive policy can be evaluated from socio-economic and climate aspects. Those aspects have been extracted from related literature and interviews with experts in the field of energy and regional development [34– 38]. According to the framework, the potential of solar radiation is examined for provinces/states. Daily solar radiation data exists in the NASA data services [43]. Based on the radiation data, provinces are ranked. The next step involves the measurement of the socio-economic readiness index. It consists of five indicators that are calculated for provinces. Data for this index is extracted from the official reports of national statistical center. The index also shows the level of technology acceptance and investment priority in the RE industry in the province/ state. Then, the efficacy of the feed-in tariffs policy is examined for 1MW solar photovoltaic power plant (as the pilot) in the provincial capitals. The output is NPV indicator (Net Present Value). Finally, the results are compared together to examine the efficiency of equal or

2.4. Research studies on the evaluation of RE policies In addition to the above policies, different research studies have been conducted to study RE and PV policies [20]. Fouquet and Johansson (2008) and Sarasa-Maestro et al. (2013) have discussed on supportive PV policies in Europe and the effect of capital subsidies in the PV market of EU [21,22]. The similar studies for different cases have been done by Erge (2001), John and Nasser (2003), and Weiss. (2003) [23–25]. The research studies conducted by Dusonchet and Telaretti (2010a,b) review the comparative economic analysis of the European support mechanism based on the economic indicators for PV [26,27]. Studies on the effectiveness of renewable energy incentive policies have been carried out by Sarzynski et al. (2012). They found cash incentives affect the rapid expansion of solar PV systems at the state level [28]. Shrimali and Jenner (2013) found tax incentives and 671

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Fig. 2. Conceptual framework of the research.

3.2.1. Energy production simulation There are different types of solar panels on the market. Crystalline (mono and poly) and thin film are two basic types of photovoltaic modules. In this paper, the 250 W-monocrystalline solar panels are selected. The efficiency of PV module is 15.3%. It has the frame area of 1.63 m2. The electrical performance of the selected module at the standard test and NOCT conditions is given in Table 2. Due to the capacity of the solar power plant, 4016 panels are estimated to generate 1 MW power. A 1000 kW-inverter with an efficiency of 98% is selected to convert DC output of PV arrays into AC. Miscellaneous losses is assumed to be 8%. Hand et al. (2012) report that land-use requirement is 4.9 acres/MWac for PV and 8.0 acres/MWac for CSP [45]. In the current work, the required land area to install a 1 MW fixed-tilt PV system is estimated 5 acres. Fixedtilt mounting is considered for the PV installation while the slope is fixed at the optimum angle for each city.

separated policies. Following each step is described in detail. 3.1. Climatic aspect Daily solar radiation (horizontal - annual) and the annual average of air temperature are two of the main inputs of technical aspect. According to RETScreen database, these parameters are provided from ground monitoring stations [44]. If the data is not available for some locations, the meteorological data can be obtained from NASA's satellites derived data [43]. In this section, the regions are ranked based on solar radiation for case study. Iran has 31 provinces. 3.2. Policy aspect The economic viability of RE-based power generation projects is of great importance from investors’ viewpoint [39–41]. To encourage the private sector for investment in RE industry, incentives are mainly defined as financial aids and subsidies by the governments. For the case study, the main policy of Iranian government to develop renewable energy technologies is feed-in tariffs mechanism [42]. To understand the suitability of the defined policy, the economic analysis of 1-MW solar PV power plant installation is carried out by RETScreen software for the capitals of Iranian provinces. RETScreen is a clean energy project analysis software that can simulate energy production and GHG emissions reduction, and perform financial analysis of the project [44]. The software is capable to calculate the economic indicators such as Net Present Value (NPV), Payback Period and Internal Rate of Return (IRR). Iran's provinces are ranked by NPV indicator showing financial profitability. PV power plant designing is the first step in the process of economic analysis (next sections).

3.2.2. Financial analysis The Net Present Value (NPV) of a project is defined as an indicator Table 2 Electrical parameters of mono-Si-Panda-YL250C-30b at standard test and NOCT conditions [69].

672

Item

STC

NOCT

Power output Voltage at Pmax Current at Pmax Open-circuit voltage Short-circuit current

250 30.5 8.20 38.1 8.71

181.6 27.6 6.58 35.1 7.02

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to determine the present value of all cash flows of an investment. Cash flows include the both inflows and outflows which are discounted at a rate based on the project's risk [46]. In other words, NPV is equal to the difference between the present values of the costs and the benefits of a project [47]. The NPV of an investment is defined by the following equations: n

NPV =

∑ t =0

Ft = (1+i )t

n

∑ t =0

Bt − Ct (1+i )t

existence of favorable investment conditions is an important factor for constructing RE-based power plants. For this purpose, the SocioEconomic (SE) readiness index is defined which is composed of five indicators including social development, general security, knowledge and skill, electricity demand and private sector involvement. 3.3.1. Social development index Despite the advantages of RE utilization, there are restrictions related to the social acceptance of RE technologies [52,53]. Local people's opposition may interrupt the construction of RE-based power plants [54]. Raising public awareness about the benefits of renewable energy technologies could increase the social acceptance of these technologies. Social development could be a proper indicator to assess the level of public awareness of a society. Firouzabadi et al. (2010) measured the level of social development for Iran's provinces by combining 12 indicators such as Gini coefficient, literacy rate, life expectancy, employment rate, urbanization rate, etc. [55]. For the current work, Iran's provinces are ranked based on social development index which was computed by using data from the article of Firouzabadi et al. (2010) [55].

(1)

where i = interest rate; Ft = cash flow; Bt = total benefits at the end of period t ; Ct = total costs at the end of period t ; n = the life span of the project. The NPV formula can be used in a continuous variation: ∞

NPV(i) =

∫t=0 (1+i)−t . r (t ) dt

(2)

where r (t ) is the rate of flowing cash, and r (t ) = 0 when the investment is over. The effective financial parameters on the economic viability of PV systems are also an important criteria in policy aspect. The initial costs of large scale PV power plant include feasibility study, PV modules, inverter, civil construction, electricity transmission lines, land purchase and, human resources training & commissioning costs. The investment cost for a solar PV power plant with the capacity of 1-MW in Iran was estimated from 2301 USD/kWp up to 2625 USD/kWp by the authors. The range is caused by the differences in some items such as the cost of land. The estimated initial cost is realistic value with respect to the investment cost of the one of the largest PV power plants in Iran. Its initial cost was 2666.5 USD /kWp. This solar PV power plant with the capacity of 514 kW is in Mallard, which is located in Alborz province, inaugurated in 2014. Malard power plant has 1836 monocrystalline panels and 51 solar inverters (9 kW) [48]. To calculate the annual cost, operation and maintenance costs, staff wages and insurances are considered. Depending on the specific circumstances of each city, the authors estimated the annual cost accounts for 4–5% of the investment cost. Inflation and interest rates were assumed 15% and 17%, respectively. Iran's annual inflation rate was 15.5% in April 2015 [49]. The loan to investment cost ratio is one fourth. A period of 5 years is considered for payback. Renewable energy power plants are exempted from paying VAT (value-added tax). However, these power plants are obliged to pay direct tax. If the power plant is located more than 30 km away from the provincial capitals, they will receive a tax deduction of 80% for 4 years. The power plants, which are in less developed regions, will receive tax-exempt status for ten years [50]. Iran's Ministry of Energy increased FiT values to enhance the competitiveness of RE-based electricity in the market in 2015 [51]. Based on the installed capacity of PV systems, FiT rates were categorized into four groups (Table 3). The tariffs are adjusted annually. The escalation rate was computed 13% by analyzing FiT rates in the past three years.

3.3.2. Knowledge and skill index Lack of experts is one of the difficulties to invest in less developed regions [56]. Due to the high level of technology, the recruitment of experts for electricity generation from renewable energy sources is crucial. On the other hand, the employment of native people decreases the annual cost of a renewable energy project. The availability of skilled and educated labors is an important factor for the successful diffusion and adoption of a new technology in the regions. To assess the level of knowledge and skill of human resources in Iran's provinces, the share of each province of total number of technical and vocational training centers is defined as an index in order to determine the level of technical knowledge of human resources of the province (Eq. (3)). Thereby, three groups of high, medium and low are classified.

Knowledge & Skill Index of province(j) total No. of tech. & voc. training centers in province(j) = × 100 total No. of tech. & voc. training centers in Iran (3) 3.3.3. General security index Because of the high initial cost of PV power plants, the installation of such technologies requires domestic and foreign investments. The security is critical for a successful investment in clean energy projects. The general security index for a province would be determined as the number of judicial files per 1000 persons in the province during the one year (Eq. (4)). The general security of Iranian provinces is categorized into three groups: high, medium and low.

General Security Index of province(j) 12

3.3. Socio-Economic aspect

=

∑k=1 No. of judicial files of province(j) in month(k) (

population of province(j) ) 1000

(4)

In addition to technical performance and economic viability, the 3.3.4. Electricity demand index Due to environmental issues, the geographical distribution of power generating facilities is different from consumers' locations. In addition to losses of transmission lines, long distance between the locations of power generation and consumption raises the probability of an interruption in the electricity supply. However, the electricity demand for constructing RE-based power plants is critical. For this purpose, the “electricity demand” index is defined to measure electricity shortage in the provinces which is equal to difference between electricity generating capacity and consumption in the province for the duration of one year (Eq. (5)). If the difference is negative, it means that the province

Table 3 FiT values for electricity generated from solar systems in Iran (Feb 2016) [51]. Item

Rated Power

FiT (USD/ kWh)

1

Solar energy with capacity of 20 kW or less (Only for consumers and limited to their connection capacity) Solar energy with capacity of 100 kW or less (Only for consumers and limited to their connection capacity) Solar Farms with capacity of 10 MW or less Solar Farms with capacity over 10 MW

0.326

2 3 4

0.291 0.225 0.186

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Table 4 Net present value (NPV) of 1-MW PV power plant installation for Iran's provinces for 25 years. Group

NPV ($)

Province

A B C

NPV > 1,250,000 950,000 < NPV < 1,250,000 600,000 < NPV < 950,000

D E

250,000 < NPV < 600,000 NPV < 0

Bushehr- Fars- Isfahan- K.Buyer Ahmad South Khorasan- Kerman- Yazd- Sistan & Baluchestan- Hormozgan- Lorestan- Qom- Markazi- Hamedan- Kurdistan- W. Azerbaijan Khuzestan- Ch. Bakhtiari- Ilam- Kermanshah- Razavi Khorasan- Semnan- North Khorasan- Alborz- Qazvin- Zanjan- East AzerbaijanArdabil Tehran- Golestan Mazandaran- Gilan

Fig. 3. AHP tree structure for the socio-economic evaluation of 31 Iranian provinces.

and greater penetration of the renewable sources like solar and wind energies. The current infrastructure of the power grid has not been designed for patching numerous distributed feed-in points. The high fluctuations in the distributed energy production as a result of clouds or dusts cause many challenges to arise for the current grid [57]. The presence of smart grid is essential for distributed electricity generation by a great many of renewable sources [58]. Economically, smart grid allows for more facilitated establishment of a systematic relationship between the suppliers (the price of the energy produced by them) and consumers (their tendency to pay) and also, it provides the both with a higher level of flexibility and complicacy in their operational strategies. A great number of the technologies are required to accommodate a smart energy grid and some of these technologies, dealt with in several articles [59–61], are now being applied.

imports electricity from neighboring areas and also, the import increases losses of power distribution network. Therefore, the establishment of PV power plants in this province has higher priority. Based on this index, Iran's provinces is grouped in four categories: high import, low import, low export and high export.

Electricity Demand Index of province(j) 8760

=

∫hour=1 (produced electrical energy)dh 8760

−

∫hour=1 (consumed electrical energy)dh

(5)

The emergence of the modern technologies such as renewable energies along with increasing consumption of electricity in Iran, the limitations of the financial resources for the purpose of renewing the power grid, the depreciated equipment of the existent grid have confronted Iran's electricity industry with new challenges [71]. In a systematic look, smart grid offers appropriate solutions for the extant grid challenges including reliability, efficiency, the flexibility of grid topology, and issues related to market regulation and green production. In terms of reliability, smart grid decreases the outage duration and frequency via the novel solutions such as the monitoring of the elements’ status, and condition-based maintenance. Such an advantage brings more reliable power supply and lower vulnerability in respect of the natural disasters or attacks on the power grid. From an environmental perspective, smart grid is seeking to find a way to remove the present barriers on the way to provide for a more widespread use of renewable and clean sources. Smart grid is designed to have two-way technologies that it makes practical to integrate renewable energy sources into the power grid. The next generation of the transmission and distribution infrastructure will be better capable of managing the bilateral electrical energy flows and facilitating the possibility of the distributed electricity generation by rooftop-mounted solar panels, diesel generators, wind turbines and other sources. Traditional grid uses one-way flow of electricity. Smart grid presents the improvement in the flexibility of the grid

3.3.5. Private sector involvement (PSI) index Despite supportive policies such as FiT, tax exemption, GHG reduction credit, investing in RE projects is still associated with risks. The most important risks for investment in RE are market risks, credit risks, liquidity risks, operational risks and political risks [62]. The regional development of RE sources depends on private sector involvement and the risk taking of local investors. The participation of private sector in the projects is various in the different regions of a country. The number of issued operation licenses for industrial units per person in the province during the one year is defined as an indicator (Eq. (6)) that shows the willingness of the private sector of the province to invest in the projects. The level of private sector involvement in Iran's provinces is classified in three groups: high, medium and low.

PSI Index of province(j) 12

=

∑k=1 No. of issued operation l icenses of province(j) in month(k) population of province(j) (6)

674

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Fig. 4. Map of Iran's provinces categorized by SE- readiness index. Source: computed and created by authors.

policies may increase costs and decline the effectiveness of the policies. The simulation results of policy (FiT) for our case study also confirm that issue. The policies have been examined by RETScreen software. The desirability of the implemented policies in each province has been determined based on NPV indicator. Table 4 shows the NPV of 1-MW PV power plant installation for 31 provinces. They have been classified

4. Data analysis The indices are calculated based on data from the latest version of Statistical Yearbook of Iran [63]. Although the governments’ policies are equally defined for all regions, some of them such as the United States, define different policies for each state/region. However, similar

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Fig. 5. Map of Iran's provinces classified by solar radiation priority. Source: created by authors with data from [43].

in the five groups: A (the best), B, C, D, E (the worst). According to the Table 4, four provinces are in the first group (A), and 2 provinces have the lowest priority for investing in photovoltaic power plant projects (E). The high number of cloudy, and rainy days, and received solar radiation are the reasons for E group [64]. The

technical performance of PV power plants is validated by comparing with Besarati et al., (2013) research [65]. They have presented the energy output and the capacity factor of a 5-megawatt photovoltaic power plant for 50 cities in Iran.

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Fig. 6. Map of provinces grouped based on the authors suggestion and desirability (1= the best, 5= the worst). Source: computed and created by authors.

socio-economic readiness index. The extracted weights of social development, knowledge and skill, public safety, private sector participation and electricity demand indicators are 0.1, 0.21, 0.18, 0.42, and 0.09, respectively. The consistency ratio (CR) for this pair-wise comparison matrix calculated by Eq. (7) is 0.04. The preference is acceptable since CR is less than 0.1.

4.1. Analysis of socio-economic readiness The socio-economic readiness index is equal to weighted average of social development, knowledge and skill, general security, electricity demand and private sector involvement indicators. To calculate the weight of each indicator, pair-wise comparison (as a step of AHP method) is used. Analytical hierarchy process (AHP) is a helpful method widely used for making multi-criteria decisions in studies related to energy [66]. Fig. 3 shows the hierarchy tree structure for the evaluation of 31 Iranian provinces with respect to five criteria of the

CR =

CI RI

(7)

where RI is the random index specified by Saaty [67,68], and CI is consistency index computed by Eq. (8). 677

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Table 5 Suggested strategies for each category extracted from the research analysis. No.

Strategy

Category (Zone)

1 2 3 4

Providing financial and legal supports for the domestic producers of solar PV system equipment Supporting research studies related to PV technology in the regional universities and academic institutions Facilitating bank guarantees for solar PV projects Allocating the portion of the government budget for the modernization of electricity transmission network to integrate distributed generation into the grid Reducing the bureaucracy of licensing for PV power plant construction

3–4 All 3–4 All

Using long-term contracts for guaranteed power purchasing: For zones 3–4: 20 year period with escalation rate= inflation rate + 5% For zones 1–2: 15 year period with escalation rate= inflation rate + 2% Developing photovoltaic technology by establishing research centers and science and technology parks

All

Decreasing land rental cost paid to Land Affairs Organization of Iran for solar PV farms: For zones 3–4: free of charge period: 5 year For zones 1–2: free of charge period: 3 year Allocating the low percentage of the electricity bills of the government buildings and energy-intensive industries for the development of large-scale PV systems Establishing special economic energy zones for domestic and international investments Reducing the duty rate for importing solar PV equipment Facilitating the conditions in the contracts for the presence of foreign investors

All

5 6

7 8

9 10 11 12

All

all

3–4 All All 3–4

Fig. 7. Aerial photos of two 7-MW solar PV power plants in Hamedan Province [51].

Fig. 8. The installed capacity of utility-scale PV facilities in Iran, 2006- Feb 2017 [70].

CI =

λ max − n n −1

Then, provinces are ranked based on the socio-economic (SE) readiness index. This includes five readiness levels (very high, high, medium, low, and very low). This means provincial readiness in the adoption and deployment of a new technology. For example, the

(8)

where n is the number of attributes, and λ max is the maximum eigen value. 678

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– The supply of 20% of the equipment of these PV power plants by the domestic manufacturers (strategy No.1) – Optimal site selection of the power plants which improves their economic viability. – The significant reduction of duty rates for importing the required equipment of the power plants (strategy No.11) – The presence of foreign investors (Germany and Ireland) in these two power-plant projects (strategy No.12) – Financially supporting the science and technology parks as well as the knowledge-based companies in Hamadan Province (strategy No.7)

availability of local skilled labor related to renewable energy projects affect the successful implementation of RE projects. The level of readiness of Iran provinces is shown in the Fig. 4. All figures have been designed via ArcGIS software. 4.2. Analysis of solar radiation potential The production of electricity from a solar PV power plant is highly dependent on solar energy input. Received solar energy is the most important climatic parameter in selecting facility site. Based on solar radiation, the priority of Iran's provinces for investment has been classified into 3 groups (Fig. 5).

This case is a practical example of the successful implementation of the regional supportive policies. Moreover, the installed capacity of utility-scale PV facilities in Iran has increased exponentially in recent two years (Fig. 8). It is important to note that the data for 2016 and 2017 was approximately collected.

4.3. Analysis of the effectiveness of solar energy supportive policies The desirability of provinces is determined with respect to the solar potential and their readiness levels (Fig. 6). According to the figure, provinces in the fifth zone have the lowest priority for investment. Provinces in first zone have the highest priority to invest in solar PV projects, and it is expected the cost of security and hiring local skilled workers to be minimum. Due to the high level of social development, local people have less resistance to clean energy projects. The possibility of private sector participation in PV projects in such provinces is more. Because of the high solar radiation in those areas, PV installations generate more power. The results show a significant difference between the effectiveness of the identical policies and the levels of readiness to adopt solar energy incentives and policies. For instance, in the case study, while provinces such as Lorestan, Hamedan, and Kurdistan are in the group B of financial profitability (Table 3) while in the desirability map (Fig. 6), they are in the poor zones. The reason is the lack of infrastructure, lack of skilled labor and low participation of the private sector in the industrial projects. Khorasan Razavi and Semnan provinces are among favorable regions for investment due to the high radiation level and the relatively good development level, while in Table 3, they are classified as Group C. These differences suggest that the same implementation of feed-in tariffs policy is not efficient for all provinces. This confirms the descriptive hypothesis of the research. Therefore, policies which are defined based on the development level of the provinces will be more successful. According to the above analysis, the policies are suggested for the five categories (zones) of the case study (Table 5).

5. Conclusions Renewable energy industries are developing but they are very vulnerable in comparison with other industries for access to capital and institutional experiences. In this study, the effectiveness of equal RE policies for the deployment of solar photovoltaic technology was examined. We analyzed the policies and presented an innovative framework to show the implementation of classified policies has higher efficiency. If the government supportive policies in all regions are equal, this status may reduce the effectiveness, especially in large countries. In such circumstances, the site selection for renewable energy plants is carried out by investors. Indeed, the governments do not distinguish between desirable areas with others and ignore to organize investments in RE technologies. While the government is capable of codifying the RE policies based on the local circumstances of each province. As future research, testing the suitability of the presented framework is suggested for different case studies. Indeed, it can be implemented for different RE sources. On the other hand, while the focus of current research was on developing one megawatt PV power plants, future research studies may focus on other scales of PV installations. Acknowledgements

4.4. A practical example of the suggested framework The authors would like to thank the respected anonymous reviewers for their valuable comments and time.

The investigations on the suitability level of Iran's provinces from three social-economic, climatic and technical aspects in regard of the establishment of a photovoltaic power plant indicate that the technically optimal provinces are not necessarily in a favorable level in terms of socio-economic readiness aspect. One such province is Hamadan. Although the received solar radiation in the province is in a high level (above 4.45 kWh/m2/day) and it is situated in the appropriate group (group B) in terms of NPV scale, but it is found in a low level in terms of its socio-economic readiness. Until late 2015, there was no photovoltaic power plant in this province. The conditions for making investments in solar photovoltaic sector were facilitated in the province through the adoption of the suggested strategies (Table 5) by the local administrative organizations in such a manner that in February 2017, two 7-MW PV power plants were inaugurated in the province by the private sector (Fig. 7). It is expected that until early 2018, three other 7-MW power plants can be installed in the province by which way the total installed photovoltaic capacity will reach to 35 MW. The followings are the strategies applied in this province for the deployment of solar energy:

References [1] Fadai D, Esfandabadi ZS, Abbasi A. Analyzing the causes of non-development of renewable energy-related industries in Iran. Renew Sustain Energy Rev 2011;15:2690–5. [2] Aslani A, Antila E, Wong Q-KF. Comparative analysis of energy security in the Nordic countries: the role of renewable energy resources in diversification. J Renew Sustain Energy 2012;4(6). [3] Devabhaktuni V, Alam M, Depuru SSSR, Green RC, Nims D, Near C. Solar energy: trends and enabling technologies. Renew Sustain Energy Rev 2013;19:555–64. [4] Aslani A, Naaranoja M, Wong KFV. Strategic analysis of diffusion of renewable energy in the Nordic countries. Renew Sustain Energy Rev 2013;22:497–505. [5] Aslani A. Private sector investment in renewable energy utilization: strategic analysis of stakeholder perspectives in developing countries. Int J Sustain Energy 2013;33:112. [6] Sen S. Renew Sustain Energy Rev 2016. http://dx.doi.org/10.1016/ j.rser.2016.09.137. [7] Luttenberger LR. The barriers to renewable energy use in Croatia. Renew Sustain Energy Rev 2015;49:646–54. [8] Luthra S, Kumar S, Garg D, Haleem A. Barriers to renewable/sustainable energy technologies adoption: indian perspective. Renew Sustain Energy Rev 2015;41:762–76. [9] Aslani A, Naaranoja M, Mohaghar A. Renewable energy industry: business aspects. Encycl Energy Eng Technol 2014. http://dx.doi.org/10.1081/E-EEE2-120051558. [10] Gmelin H, Seuring S. Determinants of a sustainable new product development. J

– Signing a 20-year contract for the guaranteed purchase of electricity from these power plants (strategy No.6) 679

Renewable and Sustainable Energy Reviews 79 (2017) 669–680

H. Hafeznia et al.

different countries. Sol Energy 2016;131:81–95. [40] Li Z, Boyle F, Reynolds A. Domestic application of solar PV systems in Ireland: the reality of their economic viability. Energy 2011;36:5865–76. [41] Byrnes L, Brown C, Wagner L, Foster J. Reviewing the viability of renewable energy in community electrification: the case of remote Western Australian communities. Renew Sustain Energy Rev 2016;59:470–81. [42] Najafi G, Ghobadian B, Mamat R, Yusaf T, Azmi WH. Solar energy in Iran: current state and outlook. Renew Sustain Energy Rev 2015;49:931–42. [43] Stackhouse P Jr., Whitlock C Surface meteorology and solar energy. A renewable energy resource web site (release6.0). URL: 〈http://eosweb.larc.nasa.gov/sse/〉. [44] RETScreen 4.0 International, Clean Energy Project Analysis software, Natural Resources Canada, available at: 〈http://www.retscreen.net〉. [45] Hand MM, Baldwin S, DeMeo E, Reilly JM, Mai T, Arent D, Porro G, Meshek M, Sandor D. Renewable electricity futures study. eds. 4 vols. NREL/TP-6A20-52409. Golden, CO: National Renewable Energy Laboratory; 2012. [46] Petković D, Shamshirband S, Kamsin A, Lee M, Anicic O, Nikolić V. Survey of the most influential parameters on the wind farm net present value (NPV) by adaptive neuro-fuzzy approach. Renew Sustain Energy Rev 2016;57:1270–8. [47] Mathur A, Agrawal GD, Chandel M. Techno-economic analysis of solar parabolic trough type energy system for garment zone of Jaipur city. Renew Sustain Energy Rev 2013;17:104–9. [48] The official site of the President of the Islamic Republic of Iran, URL: 〈http://www. president.ir/fa/80179〉 last Accessed February 2017. [49] Central Bank of the Islamic Republic of Iran, Economic Statistics, URL: 〈http:// www.cbi.ir/showitem/13040.aspx〉 last Accessed February 2017. [50] Iranian National Tax Administration (INTA), URL: 〈http://www.intamedia.ir〉. [51] Renewable Energy Organization of Iran (SUNA), URL: 〈http://www.suna.org.ir/ en/home〉. [52] Heras-Saizarbitoria I, Cilleruelo E, Zamanillo I. Public acceptance of renewables and the media: an analysis of the Spanish PV solar experience. Renew Sustain Energy Rev 2011;15(9):4685–96. [53] Wüstenhagen R, Wolsink M, Bürer MJ. Social acceptance of renewable energy innovation: an introduction to the concept. Energy Policy 2007;35(5):2683–91. [54] Ribeiro F, Ferreira P, Araújo M. The inclusion of social aspects in power planning. Renew Sustain Energy Rev 2011;15:4361–9. [55] Firouzabadi A, Hosseini R, Ghassemi R. The study of provinces social development ranking in terms of the priority of indicators and its relationship with social capital. Social Welf Q 2010;37:57–93. [56] Gabriel Cle-Anne. What is challenging renewable energy entrepreneurs in developing countries?. Renew Sustain Energy Rev 2016;64:362–71. [57] Eltigani D, Masri S. Challenges of integrating renewable energy sources to smart grids: a review. Renew Sustain Energy Rev 2015;52:770–80. [58] Hossain MS, Madlool NA, Rahim NA, Selvaraj J, Pandey AK, Khan AF. Role of smart grid in renewable energy: an overview. Renew Sustain Energy Rev 2016;60:1168–84. [59] Larik RM, Mustafa MW. Technologies used in smart grid to implement power distribution system. TELKOMNIKA Indonesian. J Electr Eng 2015;16:232–7. [60] Larik RM, Mustafa MW, Qazi SH. Smart grid technologies in power systems: an overview. Res J Appl Sci Eng Technol 2015;11:633–8. [61] Bayindir R, Colak I, Fulli G, Demirtas K. Smart grid technologies and applications. Renew Sustain Energy Rev 2016;66:499–516. [62] Lee CW, Zhong J. Financing and risk management of renewable energy projects with a hybrid bond. Renew Energy 2015;75:779–87. [63] Statistical Centre of Iran, URL: 〈http://www.amar.org.ir/english/〉. [64] Islamic republic of Iran meteorological organization, URL: 〈http://www.irimo.ir〉. [65] Besarati SM, Padilla RV, Goswami DY, Stefanakos E. The potential of harnessing solar radiation in Iran: generating solar maps and viability study of PV power plants. Renew Energy 2013;53:193–9. [66] Strantzali E, Aravossis K. Decision making in renewable energy investments: a review. Renew Sustain Energy Rev 2016;55:885–98. [67] Saaty TL. The analytic hierarchy process. New York: McGraw Hill; 1980. [68] Saaty TL, Hu G. Ranking by the eigenvector versus other methods in the analytic hierarchy process. Appl Math Lett 1998;11(4):121–5. [69] Yingli data sheet for the PV module model: mono-Si-Panda-YL250C-30b. Available at: 〈http://www.yinglisolar.com/assets/uploads/products/downloads/Yingli %20Solar_PANDA%2060%20Cell.pdf〉 Accessed February 2017. [70] Deputy of Electricity and Energy Affairs of Iran . Iran’s Ministry of energy. Iran'S Energy Balance 2014 2016. [71] Khosroshahi KA, Jadid S, Shahidehpour M. Electric power restructuring in Iran: achievements and challenges. Electr J 2009;22(2):74–83.

Clean Prod 2014;69:1–9. [11] Renewables Global Status Report. REN21. Germany. ISBN 978-3-9818107-0-7; 2016. [12] Aslani A, Mohaghar A. Business structure in renewable energy industry: key areas. Renew Sustain Energy Rev 2013;27:569–75. [13] Zhang S, Wang W, Wang L, Zhao X. Review of China's wind power firms internationalization: status quo, determinants, prospects and policy implications. Renew Sustain Energy Rev 2015;43:1333–42. [14] Global Wind Statistics Report. Global Wind Energy Council. February 2017; 2016. [15] Gosens JG, Lu YL. Prospects for global market expansion of China's wind turbine manufacturing industry. Energy Policy 2014;67:301–18. [16] Purohit P, Kandpal TC. Solar photovoltaic pumping in India: a financial evaluation. Int J Ambient Energy 2005;26(3):135–46. [17] Lewis JI. Building a national wind turbine industry: experience from China, India and South Korea. Int J Technol Glob 2011;5:281–305. [18] Mundo-Hernández J, Alonso B, Hernández-Álvarez J, Celis-Carrillo B. An overview of solar photovoltaic energy in Mexico and Germany. Renew Sustain Energy Rev 2014;31:639–49. [19] Hünnekes C, Plume K. Photovoltaic business in Germany – status and prospects. IEA, PVPS annual report 2012, 55–57. Available at:〈〈http://www.iea-pvps.org/ index.php?Id=6〉〉Accessed 19 January 2015; 2012. [20] Pirnia M, Nathwani J, Fuller D. Ontario feed-in-tariffs: system planning implications and impacts on social welfare. Electr J 2011;24:18–28. [21] Fouquet D, Johansson TB. European renewable energy policy at crossroads – focus on electricity support mechanisms. Energy Policy 2008;36:4079–92. [22] Sarasa-Maestro CJ, Dufo-Lopez R, Bernal-Agustin JL. Photovoltaic remuneration policies in the European Union. Energy Policy 2013;55:317–28. [23] Erge T, Hoffmann VU, Kiefer K. The German experience with grid-connected PVsystems. Sol Energy 2001;70:479–87. [24] Jahn U, Nasse W. Performance analysis and reliability of grid connected PV systems in IEA countries. In: Proceedings of the 3rd world conference on photovoltaic energy conversion, Osaka, Japan, pp. 2148–2151; 2003. [25] Weiss I, Sprau P, Helm P. The German PV solar financing schemes reflected on the Germany market. In: Proceedings of the 3rd world conference on photovoltaic energy conversion, Osaka, Japan, pp. 2592–2595; 2003. [26] Dusonchet L, Telaretti E. Economic analysis of different supporting policies for the production of electrical energy by solar photovoltaics in eastern European Union countries. Energy Policy 2010;38:4011–20. [27] Dusonchet L, Telaretti E. Economic analysis of different supporting policies for the production of electrical energy by solar photovoltaics in western European Union countries. Energy Policy 2010;38:3297–308. [28] Sarzynski A, Larrieu J, Sharimali G. The impact of state financial incentives on market deployment of solar technology. Energy Policy 2012;46:550–7. [29] Shrimali G, Jenner S. The impact of state policy on deployment and cost of solar photovoltaic technology in the U.S.: a sector-specific empirical analysis. Renew Energy 2013;60:679–90. [30] Kwan CL. Influence of location environmental, social, economic and political variables on the spatial distribution of residential solar PV arrays across the United States. Energy Policy 2012;47:332–44. [31] Mendonça M, Jacobs D, Sovacool B. Powering the green economy: the feed-in tariff handbook. London: Earthscan; 2010. [32] White LV, Lloyd B, Wakes SJ. Are feed in tariffs suitable for promoting solar PV in New Zealand cities?. Energy Policy 2013;60:167–78. [33] Shrimali G, Srinivasan S, Goel S, Nelson D. The effectiveness of federal renewable policies in India. Renew Sustain Energy Rev 2017;70:538–50. [34] Urmee T, Md A. Social, cultural and political dimensions of off-grid renewable energy programs in developing countries. Renew Energy 2016;93:159–67. [35] Huesca-Pérez ME, Sheinbaum-Pardo C, Köppel J. Social implications of siting wind energy in a disadvantaged region–The case of the Isthmus of Tehuantepec, Mexico. Renew Sustain Energy Rev 2016;58:952–65. [36] Luthi S. Effective deployment of photovoltaics in the Mediterranean countries: balancing policy risk and return. Sol Energy 2010;84:1059–71. [37] Markard J, et al. Socio-technical transitions and policy change – Advocacy coalitions in Swiss energy policy. Environ Innov Soc Transit 2015. http:// dx.doi.org/10.1016/j.eist.2015.05.003. [38] Bartiaux F, Schmidt L, Horta A, Correia A. Social diffusion of energy-related practices and representations: patterns and policies in Portugal and Belgium. Energy Policy 2016;88:413–21. [39] Rodrigues S, Torabikalaki R, Faria F, Cafofo N, Chen X, Ivaki AR, Mata-Lima H, Morgado-Dias F. Economic feasibility analysis of small scale PV systems in

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